{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T05:17:15Z","timestamp":1755926235403,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811322051"},{"type":"electronic","value":"9789811322068"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-981-13-2206-8_20","type":"book-chapter","created":{"date-parts":[[2018,9,8]],"date-time":"2018-09-08T10:43:21Z","timestamp":1536403401000},"page":"227-239","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Hierarchical RNN for Few-Shot Information Extraction Learning"],"prefix":"10.1007","author":[{"given":"Shengpeng","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Binbin","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,9,9]]},"reference":[{"key":"20_CR1","unstructured":"Abadi, M., et al.: Tensorflow: large-scale machine learning on heterogeneous distributed systems (2016). arXiv preprint: arXiv:1603.04467"},{"key":"20_CR2","first-page":"1137","volume":"3","author":"Y Bengio","year":"2003","unstructured":"Bengio, Y., Ducharme, R., Vincent, P., Jauvin, C.: A neural probabilistic language model. J. Mach. Learn. Res. 3, 1137\u20131155 (2003)","journal-title":"J. Mach. Learn. Res."},{"key":"20_CR3","unstructured":"Berglund, M., Raiko, T., Honkala, M., K\u00e4rkk\u00e4inen, L., Vetek, A., Karhunen, J.: Bidirectional recurrent neural networks as generative models - reconstructing gaps in time series, April 2015. arXiv:1504.01575 [cs]"},{"key":"20_CR4","doi-asserted-by":"crossref","unstructured":"Bing, L., Lam, W., Wong, T.L.: Wikipedia entity expansion and attribute extraction from the web using semi-supervised learning. In: Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, pp. 567\u2013576. ACM (2013)","DOI":"10.1145\/2433396.2433468"},{"key":"20_CR5","doi-asserted-by":"crossref","unstructured":"Cheng, J., Dong, L., Lapata, M.: Long short-term memory-networks for machine reading (2016). arXiv preprint: arXiv:1601.06733","DOI":"10.18653\/v1\/D16-1053"},{"key":"20_CR6","unstructured":"Chung, J., Gulcehre, C., Cho, K., Bengio, Y.: Empirical evaluation of gated recurrent neural networks on sequence modeling (2014). arXiv preprint: arXiv:1412.3555"},{"key":"20_CR7","doi-asserted-by":"crossref","unstructured":"Dhingra, B., Liu, H., Cohen, W.W., Salakhutdinov, R.: Gated-attention readers for text comprehension (2016). arXiv preprint: arXiv:1606.01549","DOI":"10.18653\/v1\/P17-1168"},{"issue":"4","key":"20_CR8","doi-asserted-by":"publisher","first-page":"594","DOI":"10.1109\/TPAMI.2006.79","volume":"28","author":"L Fei-Fei","year":"2006","unstructured":"Fei-Fei, L., Fergus, R., Perona, P.: One-shot learning of object categories. IEEE Trans. Pattern Anal. Mach. Intell. 28(4), 594\u2013611 (2006)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"6","key":"20_CR9","doi-asserted-by":"publisher","first-page":"801","DOI":"10.1016\/S0893-6080(05)80125-X","volume":"6","author":"KI Funahashi","year":"1993","unstructured":"Funahashi, K.I., Nakamura, Y.: Approximation of dynamical systems by continuous time recurrent neural networks. Neural Netw. 6(6), 801\u2013806 (1993)","journal-title":"Neural Netw."},{"key":"20_CR10","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1007\/978-3-319-10816-2_35","volume-title":"Text, Speech and Dialogue","author":"AL Gentile","year":"2014","unstructured":"Gentile, A.L., Zhang, Z., Ciravegna, F.: Self training wrapper induction with\u00a0linked\u00a0data. In: Sojka, P., Hor\u00e1k, A., Kope\u010dek, I., Pala, K. (eds.) TSD 2014. LNCS (LNAI), vol. 8655, pp. 285\u2013292. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10816-2_35"},{"key":"20_CR11","series-title":"IFIP Advances in Information and Communication Technology","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1007\/978-3-319-44944-9_14","volume-title":"Artificial Intelligence Applications and Innovations","author":"T Gogar","year":"2016","unstructured":"Gogar, T., Hubacek, O., Sedivy, J.: Deep neural networks for web page information extraction. In: Iliadis, L., Maglogiannis, I. (eds.) AIAI 2016. IFIP AICT, vol. 475, pp. 154\u2013163. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-44944-9_14"},{"key":"20_CR12","doi-asserted-by":"crossref","unstructured":"Hao, Q., Cai, R., Pang, Y., Zhang, L.: From one tree to a forest: a unified solution for structured web data extraction. In: Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 775\u2013784. ACM (2011)","DOI":"10.1145\/2009916.2010020"},{"key":"20_CR13","unstructured":"Hochreiter, S., Schmidhuber, J.: LSTM can solve hard long time lag problems. In: Advances in Neural Information Processing Systems, pp. 473\u2013479 (1997)"},{"key":"20_CR14","unstructured":"Kushmerick, N.: Wrapper induction for information extraction. Ph.D. thesis, University of Washington (1997)"},{"key":"20_CR15","unstructured":"Le, Q.V., Mikolov, T.: Distributed representations of sentences and documents. In: ICML, vol. 14, pp. 1188\u20131196 (2014)"},{"key":"20_CR16","unstructured":"Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space (2013). arXiv preprint: arXiv:1301.3781"},{"key":"20_CR17","doi-asserted-by":"crossref","unstructured":"Pei, W., Baltru\u0161aitis, T., Tax, D.M., Morency, L.P.: Temporal attention-gated model for robust sequence classification (2016). arXiv preprint: arXiv:1612.00385","DOI":"10.1109\/CVPR.2017.94"},{"issue":"13","key":"20_CR18","doi-asserted-by":"publisher","first-page":"2194","DOI":"10.14778\/2831360.2831372","volume":"8","author":"D Qiu","year":"2015","unstructured":"Qiu, D., Barbosa, L., Dong, X.L., Shen, Y., Srivastava, D.: Dexter: large-scale discovery and extraction of product specifications on the web. Proc. VLDB Endow. 8(13), 2194\u20132205 (2015)","journal-title":"Proc. VLDB Endow."},{"issue":"11","key":"20_CR19","doi-asserted-by":"publisher","first-page":"2673","DOI":"10.1109\/78.650093","volume":"45","author":"M Schuster","year":"1997","unstructured":"Schuster, M., Paliwal, K.K.: Bidirectional recurrent neural networks. IEEE Trans. Signal Process. 45(11), 2673\u20132681 (1997)","journal-title":"IEEE Trans. Signal Process."},{"issue":"1\u20133","key":"20_CR20","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1023\/A:1007562322031","volume":"34","author":"S Soderland","year":"1999","unstructured":"Soderland, S.: Learning information extraction rules for semi-structured and free text. Mach. Learn. 34(1\u20133), 233\u2013272 (1999)","journal-title":"Mach. Learn."},{"issue":"1","key":"20_CR21","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.datak.2008.08.009","volume":"68","author":"TL Wong","year":"2009","unstructured":"Wong, T.L., Lam, W.: An unsupervised method for joint information extraction and feature mining across different web sites. Data Knowl. Eng. 68(1), 107\u2013125 (2009). https:\/\/doi.org\/10.1016\/j.datak.2008.08.009","journal-title":"Data Knowl. Eng."},{"issue":"4","key":"20_CR22","doi-asserted-by":"publisher","first-page":"523","DOI":"10.1109\/TKDE.2009.111","volume":"22","author":"TL Wong","year":"2010","unstructured":"Wong, T.L., Lam, W.: Learning to adapt web information extraction knowledge and discovering new attributes via a Bayesian approach. IEEE Trans. Knowl. Data Eng. 22(4), 523\u2013536 (2010)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"20_CR23","doi-asserted-by":"crossref","unstructured":"Wong, T.L., Lam, W., Wong, T.S.: An unsupervised framework for extracting and normalizing product attributes from multiple web sites. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 35\u201342. ACM (2008)","DOI":"10.1145\/1390334.1390343"},{"key":"20_CR24","doi-asserted-by":"crossref","unstructured":"Yang, Z., Yang, D., Dyer, C., He, X., Smola, A., Hovy, E.: Hierarchical attention networks for document classification. In: Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2016)","DOI":"10.18653\/v1\/N16-1174"},{"key":"20_CR25","doi-asserted-by":"crossref","unstructured":"Zheng, S., Song, R., Wen, J.R., Wu, D.: Joint optimization of wrapper generation and template detection. In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 894\u2013902. ACM (2007)","DOI":"10.1145\/1281192.1281287"}],"container-title":["Communications in Computer and Information Science","Data Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-13-2206-8_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T13:08:16Z","timestamp":1710248896000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-13-2206-8_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9789811322051","9789811322068"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-13-2206-8_20","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"9 September 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}